Evidence map›Paper›PMID 34207205›Full record

ArticleInternational journal of environmental research and public health2021

The COVID-19 Pandemic Situation in Malaysia: Lessons Learned from the Perspective of Population Density.

Siew Bee Aw, Bor Tsong Teh, Gabriel Hoh Teck Ling, Pau Chung Leng, Weng Howe Chan, Mohd Hamdan Ahmad

Open access · goldAbstract readCase Reports
In one paragraph

Article in International journal of environmental research and public health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 2 pooled it
3.8field-weighted citation impact, top 6% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

12 citing papers in PubMed, 2 syntheses or guidelines pooled it, 45 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 1 institution in 1 country.

Siew Bee AwFaculty of Built Environment and Surveying, Universiti Teknologi Malaysia, Skudai 81300, Johor, Malaysia.
Bor Tsong TehFaculty of Built Environment and Surveying, Universiti Teknologi Malaysia, Skudai 81300, Johor, Malaysia.ORCID 0000-0002-8364-3110
Gabriel Hoh Teck LingFaculty of Built Environment and Surveying, Universiti Teknologi Malaysia, Skudai 81300, Johor, Malaysia.ORCID 0000-0001-5750-3336
Pau Chung LengFaculty of Built Environment and Surveying, Universiti Teknologi Malaysia, Skudai 81300, Johor, Malaysia.ORCID 0000-0003-2720-9077
Weng Howe ChanSchool of Computing, Faculty of Engineering, Universiti Teknologi Malaysia, Skudai 81300, Johor, Malaysia.
Mohd Hamdan AhmadFaculty of Built Environment and Surveying, Universiti Teknologi Malaysia, Skudai 81300, Johor, Malaysia.
University of Technology Malaysia · MY

Funding

Universiti Teknologi Malaysia (UTM) Transdisciplinary Research Grant Q.J130000.3552.07G55
6 · The paper itself

Abstract

This paper attempts to ascertain the impacts of population density on the spread and severity of COVID-19 in Malaysia. Besides describing the spatio-temporal contagion risk of the virus, ultimately, it seeks to test the hypothesis that higher population density results in exacerbated COVID-19 virulence in the community. The population density of 143 districts in Malaysia, as per data from Malaysia's 2010 population census, was plotted against cumulative COVID-19 cases and infection rates of COVID-19 cases, which were obtained from Malaysia's Ministry of Health official website. The data of these three variables were collected between 19 January 2020 and 31 December 2020. Based on the observations, districts that have high population densities and are highly inter-connected with neighbouring districts, whether geographically, socio-economically, or infrastructurally, tend to experience spikes in COVID-19 cases within weeks of each other. Using a parametric approach of the Pearson correlation, population density was found to have a moderately strong relationship to cumulative COVID-19 cases (

Indexed as

COVID-19HumansMalaysiaPandemicsPopulation DensitySARS-CoV-2coronavirusCOVID-19Malaysianon-pharmaceutical measuresPearson correlationspopulation densityspatio-temporal

Identifiers

PMID34207205
PMCPMC8296337
OpenAlexW3177096825

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.